class_docstr: Sampling-based super-net training but using an RL agent to control the sampling.
  
  The default implementation for :class:`~nni.nas.strategy.ENAS`.
  
  See Also
  --------
  nni.nas.strategy.ENAS
  RandomSamplingLightningModule
docstr: Run one more inference of ENAS controller.
docstr_tok: ["Run","one","more","inference","of","ENAS","controller","."]
code: def export(self):
      """Run one more inference of ENAS controller."""
      self.policy.eval()
      with torch.no_grad():
          return self.generator.next_sample()
  
imports: from __future__ import annotations
  import warnings
  import logging
  from typing import Any, Callable, TYPE_CHECKING
  import pytorch_lightning
  import torch
  from nni.mutable import Sample
  from nni.nas.nn.pytorch import ModelSpace
  from .base_lightning import BaseOneShotLightningModule
  from .profiler import ProfilerPenalty, ExpectationProfilerPenalty, SampleProfilerPenalty
label_desc: Use image node_id 8 for calling the EnasLightningModule obj's underlying member method code with example usage: obj.export() and returns: self